Introduction to Python GIS

Lesson 4

Reading KML-files in Geopandas

import geopandas as gpd
import matplotlib.pyplot as plt
gpd.io.file.fiona.drvsupport.supported_drivers['KML'] = 'rw'

polys = gpd.read_file('PKS_suuralue.kml', driver='KML')

/Users/lchen/anaconda3/envs/geo_env/lib/python3.8/site-packages/geopandas/geodataframe.py:422: RuntimeWarning: Sequential read of iterator was interrupted. Resetting iterator. This can negatively impact the performance.
  for feature in features_lst:

polys.plot()

<AxesSubplot:>

import pandas as pd
data = pd.read_csv('addresses.txt', sep=';')

from geopandas.tools import geocode
geo = geocode(data['addr'])

join = geo.join(data)

join.head()

	geometry	address	id	addr
0	POINT (24.91441 60.16320)	Itämerenkatu 14, 00180 Helsinki, Finland	1000	Itämerenkatu 14, 00101 Helsinki, Finland
1	POINT (24.93041 60.16860)	Kampinkuja 1, 00100 Helsinki, Finland	1001	Kampinkuja 1, 00100 Helsinki, Finland
2	POINT (24.94141 60.16999)	Kaivokatu 8, 00100 Helsinki, Finland	1002	Kaivokatu 8, 00101 Helsinki, Finland
3	POINT (24.97441 60.19530)	Hermannin rantatie, Helsinki, Finland	1003	Hermannin rantatie 1, 00580 Helsinki, Finland
4	POINT (24.92154 60.15670)	Tyynenmerenkatu 9, 00220 Helsinki, Finland	1005	Tyynenmerenkatu 9, 00220 Helsinki, Finland

southern = polys[polys['Name']=='Eteläinen']
southern.reset_index(drop=True, inplace=True)
southern.head()

	Name	Description	geometry
0	Eteläinen		POLYGON Z ((24.78277 60.09997 0.00000, 24.8197...

fig, ax = plt.subplots()

polys.plot(ax=ax, facecolor='gray');

southern.plot(ax=ax, facecolor='red');

join.plot(ax=ax, color='blue', markersize=5);

# makes some of the spatial queries running faster
import shapely.speedups
shapely.speedups.enable()

pip_mask = join.within(southern.loc[0, 'geometry'])
pip_data = join[pip_mask]
pip_data.head()

	geometry	address	id	addr
0	POINT (24.91441 60.16320)	Itämerenkatu 14, 00180 Helsinki, Finland	1000	Itämerenkatu 14, 00101 Helsinki, Finland
1	POINT (24.93041 60.16860)	Kampinkuja 1, 00100 Helsinki, Finland	1001	Kampinkuja 1, 00100 Helsinki, Finland
2	POINT (24.94141 60.16999)	Kaivokatu 8, 00100 Helsinki, Finland	1002	Kaivokatu 8, 00101 Helsinki, Finland
4	POINT (24.92154 60.15670)	Tyynenmerenkatu 9, 00220 Helsinki, Finland	1005	Tyynenmerenkatu 9, 00220 Helsinki, Finland
10	POINT (24.94241 60.17190)	Rautatientori 1, 00170 Helsinki, Finland	1011	Rautatientori 1, 00100 Helsinki, Finland

fig, ax = plt.subplots()

polys.plot(ax=ax, facecolor='gray');

southern.plot(ax=ax, facecolor='red');

pip_data.plot(ax=ax, color='gold', markersize=2);

Spatial join

• Getting attributes from one layer and transferring them into another layer based on their spatial relationship

Nearest Points

unary_union = join.unary_union
type(unary_union)

shapely.geometry.multipoint.MultiPoint

polys['centroid'] = polys.centroid

<ipython-input-60-6015d0ace0b9>:1: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  polys['centroid'] = polys.centroid

from shapely.ops import nearest_points
nearest = join['geometry'] == nearest_points(polys['geometry'][0], unary_union)[1]
join[nearest]['id']

0    1000
Name: id, dtype: int64

polys['geometry'][0]

join.head()

	geometry	address	id	addr
0	POINT (24.91441 60.16320)	Itämerenkatu 14, 00180 Helsinki, Finland	1000	Itämerenkatu 14, 00101 Helsinki, Finland
1	POINT (24.93041 60.16860)	Kampinkuja 1, 00100 Helsinki, Finland	1001	Kampinkuja 1, 00100 Helsinki, Finland
2	POINT (24.94141 60.16999)	Kaivokatu 8, 00100 Helsinki, Finland	1002	Kaivokatu 8, 00101 Helsinki, Finland
3	POINT (24.97441 60.19530)	Hermannin rantatie, Helsinki, Finland	1003	Hermannin rantatie 1, 00580 Helsinki, Finland
4	POINT (24.92154 60.15670)	Tyynenmerenkatu 9, 00220 Helsinki, Finland	1005	Tyynenmerenkatu 9, 00220 Helsinki, Finland

Reference

• Introduction to Python GIS